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Writing documentation for AI: best practices


Retrieval-Augmented Generation (RAG) systems like Kapa rely on your

A large or overly broad context increases the likelihood that the model overlooks or misinterprets critical information, resulting in reduced accuracy and less coherent outputs. Creating documentation that serves both human readers and AI effectively centers on a fundamental principle: explicit, self-contained content that maintains clear relationships between concepts. Eliminating contextual dependencies, ensuring discoverability, filling knowledge gaps, and providing text alternatives for visual content help mitigate inherent limitations in how machines consume your docs.

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